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A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma

BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. Various lncRNAs are associated with tumour biological processes, including lung adenocarcinoma (LUAD), but the role of autophagy-related lncRNAs (ARlncRNAs) in LUAD has not been fully elucidated. Thus, this study aimed to constru...

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Autores principales: Gong, Zetian, Li, Qifan, Li, Jun, Xie, Jiaheng, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841483/
https://www.ncbi.nlm.nih.gov/pubmed/35261881
http://dx.doi.org/10.21037/tcr-21-1554
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author Gong, Zetian
Li, Qifan
Li, Jun
Xie, Jiaheng
Wang, Wei
author_facet Gong, Zetian
Li, Qifan
Li, Jun
Xie, Jiaheng
Wang, Wei
author_sort Gong, Zetian
collection PubMed
description BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. Various lncRNAs are associated with tumour biological processes, including lung adenocarcinoma (LUAD), but the role of autophagy-related lncRNAs (ARlncRNAs) in LUAD has not been fully elucidated. Thus, this study aimed to construct a prognostic signature based on ARlncRNAs for LUAD. METHODS: The RNA-seq (FPKM) data and clinical information of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database. After differentially expressed lncRNAs in tumour and normal groups were identified, cox regression analyses were performed to construct a prognostic signature which was then assessed through independent prognostic analysis and functional enrichment analysis. Moreover, based on the mRNAs co-expressed with the ARlncRNAs, several potential small molecule drugs were explored in the Connectivity map (Cmap). RESULTS: A signature consisting of seven ARlncRNAs (FAM83A−AS1, LINC01116, ILF3-DT, EBLN3P, AL161785.1, AC092279.1 and AC026355.2) was constructed to predict overall survival (OS) for LUAD. The signature was identified to be independent by the cox regression analysis and obtained the largest area under the curve (AUC =0.721) in the receiver operating characteristic (ROC). Six small molecule drugs (MS-275, methotrexate, desipramine, benzbromarone, rifampicin and doxazosin) were selected from Cmap. CONCLUSIONS: A novel ARlncRNA signature for LUAD prognostic prediction was constructed, which had better efficacy than the TNM stage and used to propose potential therapeutic regimens for LUAD patients.
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spelling pubmed-88414832022-03-07 A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma Gong, Zetian Li, Qifan Li, Jun Xie, Jiaheng Wang, Wei Transl Cancer Res Original Article BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. Various lncRNAs are associated with tumour biological processes, including lung adenocarcinoma (LUAD), but the role of autophagy-related lncRNAs (ARlncRNAs) in LUAD has not been fully elucidated. Thus, this study aimed to construct a prognostic signature based on ARlncRNAs for LUAD. METHODS: The RNA-seq (FPKM) data and clinical information of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database. After differentially expressed lncRNAs in tumour and normal groups were identified, cox regression analyses were performed to construct a prognostic signature which was then assessed through independent prognostic analysis and functional enrichment analysis. Moreover, based on the mRNAs co-expressed with the ARlncRNAs, several potential small molecule drugs were explored in the Connectivity map (Cmap). RESULTS: A signature consisting of seven ARlncRNAs (FAM83A−AS1, LINC01116, ILF3-DT, EBLN3P, AL161785.1, AC092279.1 and AC026355.2) was constructed to predict overall survival (OS) for LUAD. The signature was identified to be independent by the cox regression analysis and obtained the largest area under the curve (AUC =0.721) in the receiver operating characteristic (ROC). Six small molecule drugs (MS-275, methotrexate, desipramine, benzbromarone, rifampicin and doxazosin) were selected from Cmap. CONCLUSIONS: A novel ARlncRNA signature for LUAD prognostic prediction was constructed, which had better efficacy than the TNM stage and used to propose potential therapeutic regimens for LUAD patients. AME Publishing Company 2022-01 /pmc/articles/PMC8841483/ /pubmed/35261881 http://dx.doi.org/10.21037/tcr-21-1554 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Gong, Zetian
Li, Qifan
Li, Jun
Xie, Jiaheng
Wang, Wei
A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title_full A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title_fullStr A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title_full_unstemmed A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title_short A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma
title_sort novel signature based on autophagy-related lncrna for prognostic prediction and candidate drugs for lung adenocarcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841483/
https://www.ncbi.nlm.nih.gov/pubmed/35261881
http://dx.doi.org/10.21037/tcr-21-1554
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